A Comparison Between Coupled and Decoupled Vehicle Motion Controllers Based on Prediction Models

Abstract

In this work, a comparative study is carried out with two different predictive controllers that consider the longitudinal jerk and steering rate change as additional parameters, as additional parameters, so that comfort constraints can be included. Furthermore, the approaches are designed so that the effect of longitudinal and lateral motion control coupling can be analyzed. This way, the first controller is a longitudinal and lateral coupled MPC approach based on a kinematic model of the vehicle, while the second is a decoupled strategy based on a triple integrator model based on MPC for the longitudinal control and a double proportional curvature control for the lateral motion control. The control architecture and motion planning are exhaustively explained. The comparative study is carried out using a test vehicle, whose dynamics and low-level controllers have been simulated using the realistic simulation environment Dynacar. The performed tests demonstrate the effectiveness of both approaches in speeds higher than 30 km/h, and demonstrate that the coupled strategy provides better performance than the decoupled one. The relevance of this work relies in the contribution of vehicle motion controllers considering the comfort and its advantage over decoupled alternatives for future implementation in real vehicles.

Longitudinal and lateral collision avoidance control strategy for intelligent vehicles

“…But it brings more complex control system, which leads to poor real-time performance of the system. 21 Active collision avoidance is a relatively emergency working condition, which requires high accuracy and real-time control. Existing decentralized and centralized control methods are limited by their own shortcomings and can hardly meet the control requirements of this paper.…”